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    • Python [conda env:base] *
      • Untitled4.ipynb (f42694b4)
        • Untitled4.ipynb
      • Social media Analysis.ipynb (8c44abd1)
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          Social media Analysis.ipynb

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          /DA Python/
          Name
          ...
          ModifiedLast Modified
          File Size
          • DA.ipynblast mo.32.3 KB
          • DA6intropython.ipynb2mo ago5.5 KB
          • Social media Analysis.ipynb6m ago245.3 KB
          • Untitled.ipynblast mo.72 B
          • Untitled1.ipynblast mo.154 KB
          • Untitled2.ipynblast mo.99 KB
          • Untitled3.ipynb6d ago121.9 KB
          • airquality.csv2mo ago5.2 KB
          • Bakery.csv2mo ago1 MB
          • Customer-Churn-Records.csvlast mo.817.8 KB
          • diabetes.csvlast mo.22.6 KB
          • social_media_analysis.py6m ago84.8 KB
          • social_media_engagement1.csvyesterday6.3 KB
          • untitled.txt2mo ago0 B
          • Social media Analysis.ipynb
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          Python [conda env:base] *
          Kernel status: Idle Executed 2 cellsElapsed time: 3 seconds
            [1]:
            import pandas as pd
            [2]:
            import seaborn as sns
            [3]:
            df = pd.read_csv("social_media_engagement1.csv")
            [4]:
            df
            [4]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            0 1 Facebook image 8/17/2023 14:45 2121 474 628 Thursday positive
            1 2 Facebook carousel 5/14/2023 0:45 3660 432 694 Sunday neutral
            2 3 Instagram poll 2/21/2023 16:15 4955 408 688 Tuesday negative
            3 4 Twitter image 11/16/2023 0:45 1183 90 187 Thursday negative
            4 5 Twitter video 5/23/2023 0:30 3499 247 286 Tuesday positive
            ... ... ... ... ... ... ... ... ... ...
            95 96 Instagram carousel 7/12/2023 17:45 36 294 911 Wednesday positive
            96 97 Twitter video 10/27/2023 23:45 314 108 458 Friday neutral
            97 98 Twitter text 8/5/2023 8:45 229 179 38 Saturday positive
            98 99 Instagram poll 12/29/2023 12:15 5000 500 204 Friday positive
            99 100 Instagram image 6/6/2023 21:00 4483 357 25 Tuesday neutral

            100 rows × 9 columns

            [5]:
            df.shape
            [5]:
            (100, 9)
            <class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 9 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   post_id          100 non-null    int64 
 1   platform         100 non-null    object
 2   post_type        100 non-null    object
 3   post_time        100 non-null    object
 4   likes            100 non-null    int64 
 5   comments         100 non-null    int64 
 6   shares           100 non-null    int64 
 7   post_day         100 non-null    object
 8   sentiment_score  100 non-null    object
dtypes: int64(4), object(5)
memory usage: 7.2+ KB
            [7]:
            Index(['post_id', 'platform', 'post_type', 'post_time', 'likes', 'comments',
       'shares', 'post_day', 'sentiment_score'],
      dtype='object')
            [8]:
            post_id likes comments shares
            count 100.000000 100.000000 100.00000 100.000000
            mean 50.500000 2381.810000 202.66000 415.650000
            std 29.011492 1632.573284 138.84067 283.877601
            min 1.000000 15.000000 10.00000 16.000000
            25% 25.750000 895.750000 89.75000 183.000000
            50% 50.500000 2220.000000 171.00000 356.500000
            75% 75.250000 3593.250000 299.00000 689.500000
            max 100.000000 5000.000000 500.00000 993.000000
            [9]:
            post_id            0
platform           0
post_type          0
post_time          0
likes              0
comments           0
shares             0
post_day           0
sentiment_score    0
dtype: int64
            [10]:
            platform
Instagram    36
Facebook     32
Twitter      32
Name: count, dtype: int64
            [12]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            2 3 Instagram poll 2/21/2023 16:15 4955 408 688 Tuesday negative
            5 6 Instagram carousel 5/5/2023 20:00 256 186 211 Friday neutral
            6 7 Instagram image 2/26/2023 11:45 1982 30 906 Sunday positive
            7 8 Instagram text 10/28/2023 19:30 1274 45 216 Saturday neutral
            16 17 Instagram poll 7/5/2023 5:15 2872 10 736 Wednesday positive
            23 24 Instagram carousel 1/1/2023 20:00 5000 80 399 Sunday positive
            26 27 Instagram text 10/6/2023 10:00 3161 162 137 Friday positive
            31 32 Instagram image 7/1/2023 14:45 4665 202 183 Saturday positive
            34 35 Instagram image 6/6/2023 19:30 1309 201 852 Tuesday negative
            39 40 Instagram carousel 8/4/2023 12:45 447 333 845 Friday negative
            41 42 Instagram video 11/23/2023 2:00 4929 252 730 Thursday negative
            43 44 Instagram text 7/6/2023 8:00 3259 50 177 Thursday negative
            45 46 Instagram text 5/16/2023 22:15 2251 380 427 Tuesday positive
            49 50 Instagram text 7/12/2023 0:00 1551 206 127 Wednesday negative
            53 54 Instagram image 1/21/2023 1:00 4297 360 825 Saturday negative
            55 56 Instagram image 3/13/2023 23:15 3401 190 230 Monday negative
            56 57 Instagram video 7/13/2023 9:15 4846 134 498 Thursday neutral
            59 60 Instagram carousel 5/19/2023 4:30 4763 332 956 Friday positive
            60 61 Instagram video 12/31/2023 22:30 3544 167 761 Sunday negative
            63 64 Instagram carousel 4/19/2023 19:45 130 452 724 Wednesday neutral
            64 65 Instagram image 9/20/2023 6:00 3982 314 326 Wednesday positive
            67 68 Instagram video 12/28/2023 16:45 560 486 677 Thursday negative
            70 71 Instagram video 4/10/2023 0:00 3398 261 630 Monday neutral
            73 74 Instagram video 4/14/2023 10:30 5000 454 744 Friday positive
            75 76 Instagram text 7/27/2023 19:15 2153 81 114 Thursday neutral
            77 78 Instagram poll 1/19/2023 7:15 2990 30 365 Thursday positive
            78 79 Instagram carousel 12/13/2023 4:45 4678 189 785 Wednesday positive
            81 82 Instagram carousel 11/19/2023 12:30 4656 314 757 Sunday negative
            82 83 Instagram video 12/6/2023 4:00 5000 173 792 Wednesday negative
            86 87 Instagram text 5/23/2023 22:30 15 70 454 Tuesday neutral
            89 90 Instagram poll 3/19/2023 4:00 3195 109 243 Sunday negative
            92 93 Instagram carousel 5/7/2023 0:30 951 432 734 Sunday negative
            94 95 Instagram poll 3/7/2023 19:15 3005 124 517 Tuesday positive
            95 96 Instagram carousel 7/12/2023 17:45 36 294 911 Wednesday positive
            98 99 Instagram poll 12/29/2023 12:15 5000 500 204 Friday positive
            99 100 Instagram image 6/6/2023 21:00 4483 357 25 Tuesday neutral
            [13]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            2 3 Instagram poll 2/21/2023 16:15 4955 408 688 Tuesday negative
            5 6 Instagram carousel 5/5/2023 20:00 256 186 211 Friday neutral
            6 7 Instagram image 2/26/2023 11:45 1982 30 906 Sunday positive
            7 8 Instagram text 10/28/2023 19:30 1274 45 216 Saturday neutral
            16 17 Instagram poll 7/5/2023 5:15 2872 10 736 Wednesday positive
            [15]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            0 1 Facebook image 8/17/2023 14:45 2121 474 628 Thursday positive
            1 2 Facebook carousel 5/14/2023 0:45 3660 432 694 Sunday neutral
            8 9 Facebook video 5/2/2023 6:15 317 249 221 Tuesday neutral
            12 13 Facebook carousel 11/11/2023 15:45 45 78 375 Saturday negative
            14 15 Facebook carousel 1/9/2023 20:00 889 314 262 Monday positive
            19 20 Facebook image 2/2/2023 16:00 455 86 79 Thursday positive
            25 26 Facebook carousel 10/5/2023 6:30 1992 70 515 Thursday negative
            27 28 Facebook poll 3/1/2023 8:00 2083 500 388 Wednesday neutral
            28 29 Facebook image 1/7/2023 10:30 548 153 731 Saturday negative
            29 30 Facebook carousel 2/3/2023 0:30 4594 216 739 Friday positive
            30 31 Facebook poll 9/10/2023 13:45 4795 449 978 Sunday negative
            35 36 Facebook video 4/8/2023 19:15 5000 500 43 Saturday positive
            36 37 Facebook video 5/11/2023 0:30 4245 59 83 Thursday neutral
            38 39 Facebook video 1/1/2023 6:00 5000 430 980 Sunday neutral
            46 47 Facebook poll 8/8/2023 17:45 4726 44 993 Tuesday negative
            47 48 Facebook video 3/22/2023 3:15 5000 232 16 Wednesday negative
            57 58 Facebook video 12/27/2023 4:00 2204 116 728 Wednesday neutral
            61 62 Facebook carousel 1/27/2023 15:45 3742 227 849 Friday negative
            65 66 Facebook text 1/3/2023 3:00 2265 39 318 Tuesday positive
            66 67 Facebook carousel 4/23/2023 8:15 2026 390 165 Sunday negative
            69 70 Facebook text 6/12/2023 9:30 3094 86 965 Monday negative
            71 72 Facebook carousel 5/5/2023 16:45 1690 257 656 Friday neutral
            72 73 Facebook text 7/18/2023 22:00 3026 11 761 Tuesday positive
            74 75 Facebook video 7/26/2023 20:15 5000 500 404 Wednesday positive
            79 80 Facebook text 6/25/2023 15:15 553 320 312 Sunday positive
            80 81 Facebook video 1/4/2023 18:30 2642 33 413 Wednesday neutral
            83 84 Facebook carousel 10/3/2023 19:00 1203 263 417 Tuesday negative
            84 85 Facebook text 7/6/2023 7:00 2566 368 304 Thursday neutral
            87 88 Facebook text 5/3/2023 12:30 3404 244 67 Wednesday positive
            90 91 Facebook carousel 9/15/2023 0:45 3956 402 462 Friday negative
            91 92 Facebook video 2/23/2023 17:15 1857 216 344 Thursday positive
            93 94 Facebook image 11/27/2023 4:30 1694 207 290 Monday positive
            [16]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            0 1 Facebook image 8/17/2023 14:45 2121 474 628 Thursday positive
            1 2 Facebook carousel 5/14/2023 0:45 3660 432 694 Sunday neutral
            8 9 Facebook video 5/2/2023 6:15 317 249 221 Tuesday neutral
            12 13 Facebook carousel 11/11/2023 15:45 45 78 375 Saturday negative
            14 15 Facebook carousel 1/9/2023 20:00 889 314 262 Monday positive
            [18]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            3 4 Twitter image 11/16/2023 0:45 1183 90 187 Thursday negative
            4 5 Twitter video 5/23/2023 0:30 3499 247 286 Tuesday positive
            9 10 Twitter carousel 5/11/2023 11:00 1878 225 438 Thursday neutral
            10 11 Twitter text 12/8/2023 2:15 1446 44 52 Friday negative
            11 12 Twitter video 6/15/2023 3:15 304 42 89 Thursday positive
            13 14 Twitter text 9/30/2023 10:30 1333 144 123 Saturday positive
            15 16 Twitter image 2/10/2023 13:00 2348 154 18 Friday neutral
            17 18 Twitter text 7/23/2023 5:45 512 123 338 Sunday neutral
            18 19 Twitter text 11/20/2023 2:00 2013 122 183 Monday positive
            20 21 Twitter poll 5/2/2023 6:15 559 136 55 Tuesday neutral
            21 22 Twitter carousel 1/30/2023 13:30 1961 44 439 Monday positive
            22 23 Twitter text 10/2/2023 12:15 332 109 348 Monday positive
            24 25 Twitter poll 5/17/2023 0:15 898 130 480 Wednesday positive
            32 33 Twitter video 9/27/2023 19:00 119 147 240 Wednesday positive
            33 34 Twitter poll 2/9/2023 15:30 2253 162 28 Thursday positive
            37 38 Twitter poll 5/2/2023 0:30 2463 187 445 Tuesday positive
            40 41 Twitter carousel 12/27/2023 11:30 667 176 461 Wednesday positive
            42 43 Twitter carousel 3/31/2023 16:00 2586 97 85 Friday positive
            44 45 Twitter video 12/1/2023 10:00 2236 132 118 Friday positive
            48 49 Twitter image 4/17/2023 15:00 725 169 298 Monday neutral
            50 51 Twitter text 2/14/2023 18:00 1268 73 251 Tuesday positive
            51 52 Twitter image 7/14/2023 15:00 950 113 327 Friday positive
            52 53 Twitter video 11/12/2023 17:30 1498 46 96 Sunday positive
            54 55 Twitter carousel 10/2/2023 23:30 592 34 496 Monday neutral
            58 59 Twitter video 12/24/2023 7:45 344 99 194 Sunday neutral
            62 63 Twitter image 5/15/2023 6:30 227 163 127 Monday neutral
            68 69 Twitter image 10/14/2023 18:45 187 89 284 Saturday neutral
            76 77 Twitter carousel 7/5/2023 18:15 3571 102 96 Wednesday positive
            85 86 Twitter text 11/25/2023 7:30 2416 50 62 Saturday positive
            88 89 Twitter carousel 5/3/2023 8:00 2884 197 339 Wednesday positive
            96 97 Twitter video 10/27/2023 23:45 314 108 458 Friday neutral
            97 98 Twitter text 8/5/2023 8:45 229 179 38 Saturday positive
            [19]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            3 4 Twitter image 11/16/2023 0:45 1183 90 187 Thursday negative
            4 5 Twitter video 5/23/2023 0:30 3499 247 286 Tuesday positive
            9 10 Twitter carousel 5/11/2023 11:00 1878 225 438 Thursday neutral
            10 11 Twitter text 12/8/2023 2:15 1446 44 52 Friday negative
            11 12 Twitter video 6/15/2023 3:15 304 42 89 Thursday positive
            [21]:
            platform sum mean count
            0 Facebook 15180 474.375000 32
            1 Instagram 18906 525.166667 36
            2 Twitter 7479 233.718750 32
            [22]:
            <Axes: xlabel='platform', ylabel='shares'>
            [24]:
            platform sum mean count
            0 Facebook 86392 2699.750000 32
            1 Instagram 107994 2999.833333 36
            2 Twitter 43795 1368.593750 32
            [25]:
            <Axes: xlabel='platform', ylabel='likes'>
            [27]:
            platform sum mean count
            0 Facebook 7965 248.906250 32
            1 Instagram 8368 232.444444 36
            2 Twitter 3933 122.906250 32
            [28]:
            <Axes: xlabel='platform', ylabel='comments'>
            [29]:
            post_id platform post_type post_time likes comments shares post_day sentiment_score
            0 1 Facebook image 8/17/2023 14:45 2121 474 628 Thursday positive
            1 2 Facebook carousel 5/14/2023 0:45 3660 432 694 Sunday neutral
            2 3 Instagram poll 2/21/2023 16:15 4955 408 688 Tuesday negative
            3 4 Twitter image 11/16/2023 0:45 1183 90 187 Thursday negative
            4 5 Twitter video 5/23/2023 0:30 3499 247 286 Tuesday positive
            ... ... ... ... ... ... ... ... ... ...
            95 96 Instagram carousel 7/12/2023 17:45 36 294 911 Wednesday positive
            96 97 Twitter video 10/27/2023 23:45 314 108 458 Friday neutral
            97 98 Twitter text 8/5/2023 8:45 229 179 38 Saturday positive
            98 99 Instagram poll 12/29/2023 12:15 5000 500 204 Friday positive
            99 100 Instagram image 6/6/2023 21:00 4483 357 25 Tuesday neutral

            100 rows × 9 columns

            [31]:
            platform sum mean count
            0 Facebook 1649 51.531250 32
            1 Instagram 2069 57.472222 36
            2 Twitter 1332 41.625000 32
            [32]:
            <Axes: xlabel='platform', ylabel='post_id'>
            [34]:
            sentiment_score sum mean count
            0 negative 1384 51.259259 27
            1 neutral 1337 49.518519 27
            2 positive 2329 50.630435 46
            [35]:
            <Axes: xlabel='sentiment_score', ylabel='post_id'>
            [36]:
            sentiment_score
positive    46
neutral     27
negative    27
Name: count, dtype: int64
            [38]:
            sentiment_score sum mean count
            0 negative 1384 51.259259 27
            1 neutral 1337 49.518519 27
            2 positive 2329 50.630435 46
            [39]:
            <Axes: xlabel='sentiment_score', ylabel='count'>
            [40]:
            <Axes: xlabel='sentiment_score', ylabel='post_id'>
            [41]:
            <Axes: ylabel='Count'>
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              Social media Analysis.ipynb
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